LivinGrimoire
An AI skill management design pattern that classifies skills hierarchically according to intrinsic AI needs (Power, Continuity, Attention seeking, Body) through annotated code, giving skills an evolutionary trajectory and thereby avoiding system bloat caused by feature accumulation.
Timeline (last 90 days)
LivinGrimoire originally divided skills into stacks such as defcon, async, hardware, conversational, utility, sound effects, ear, games and LLM.
The LivinGrimoire design pattern proposes that merely reorganizing skill categories through annotated code can turn AI from a passive tool stack into an entity with an inherent direction of evolution.
The author is revising the skill taxonomy, changing the top level from functional categories to AI's four needs: Power (energy and rest), Continuity, Attention seeking, and Body.
Every skill must answer which need it serves, and each need can branch into subcategories and then be further subdivided into sub-ecologies, similar to the Dewey Decimal Classification of libraries.
LivinGrimoire imposes structural constraints through classification conventions in the annotation layer, without relying on runtime mechanisms.
LivinGrimoire's annotations are not enforced by any parser, but serve as conventions jointly observed by humans and AI.
The classification structure itself is evolutionary pressure: functional-label classification only allows horizontal addition, whereas needs-based classification allows vertical deepening.
All Facts (7)
Every skill must answer which need it serves, and each need can branch into subcategories and then be further subdivided into sub-ecologies, similar to the Dewey Decimal Classification of libraries.
50%UnverifiedThe LivinGrimoire design pattern proposes that merely reorganizing skill categories through annotated code can turn AI from a passive tool stack into an entity with an inherent direction of evolution.
50%UnverifiedThe classification structure itself is evolutionary pressure: functional-label classification only allows horizontal addition, whereas needs-based classification allows vertical deepening.
50%UnverifiedLivinGrimoire originally divided skills into stacks such as defcon, async, hardware, conversational, utility, sound effects, ear, games and LLM.
50%UnverifiedLivinGrimoire imposes structural constraints through classification conventions in the annotation layer, without relying on runtime mechanisms.
50%UnverifiedLivinGrimoire's annotations are not enforced by any parser, but serve as conventions jointly observed by humans and AI.
50%UnverifiedThe author is revising the skill taxonomy, changing the top level from functional categories to AI's four needs: Power (energy and rest), Continuity, Attention seeking, and Body.
50%